Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "48"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 48 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 51 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 49 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 48, Node N06:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2459866 not_connected 100.00% 0.00% 0.00% 0.00% - - 2.904472 3.233092 23.091020 27.462191 2.078619 1.527409 -1.184372 -2.249529 0.6810 0.6715 0.4088 nan nan
2459865 not_connected 100.00% 0.00% 0.00% 0.00% - - 4.914315 3.896774 29.589316 36.936844 3.915458 6.198334 6.856215 5.697046 0.7010 0.6917 0.3825 nan nan
2459864 not_connected 100.00% 0.00% 0.00% 0.00% - - 7.830430 9.348158 24.431078 24.494026 5.483175 8.947288 -5.934556 -6.272246 0.6751 0.6532 0.4293 nan nan
2459863 not_connected 100.00% 0.00% 0.00% 0.00% - - 4.299793 5.307999 4.147923 4.022896 1.585015 2.104827 -3.200759 -4.023477 0.6720 0.6475 0.4164 nan nan
2459862 not_connected 100.00% 0.00% 0.00% 0.00% - - 5.908738 7.002335 29.464767 29.267047 7.478318 12.620876 -2.536284 -3.092680 0.6579 0.6842 0.4299 nan nan
2459861 not_connected 0.00% 0.00% 0.00% 0.00% - - 3.109155 3.716508 2.833104 2.473712 0.585942 0.217655 -3.900575 -4.402133 0.6868 0.6636 0.4294 nan nan
2459860 not_connected 100.00% 0.00% 0.00% 0.00% - - 4.590615 5.097160 22.435510 22.125633 10.323019 14.678188 -2.299890 -3.351786 0.6866 0.6562 0.4272 nan nan
2459859 not_connected 0.00% 0.00% 0.00% 0.00% - - 3.061670 3.130500 2.915110 2.464707 0.835001 0.216629 -2.412524 -2.922979 0.6933 0.6610 0.4226 nan nan
2459858 not_connected 0.00% 0.00% 0.00% 0.00% 100.00% 0.00% 3.042627 3.468368 2.634102 2.294387 0.585636 -0.285007 -4.229243 -4.508992 0.7050 0.6687 0.4347 2.834957 2.638903
2459857 not_connected 100.00% 100.00% 100.00% 0.00% - - 25.011257 24.319911 11.192288 11.234026 11.908282 12.644056 47.511844 49.794054 0.0329 0.0333 0.0001 nan nan
2459856 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 6.456241 6.571342 20.579751 20.140595 4.427210 7.416480 -3.855797 -4.192125 0.6929 0.6816 0.4195 2.539507 2.367029
2459855 not_connected 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 75.881435 75.479274 inf inf 4363.644384 4363.637796 4165.170593 4164.518655 0.0078 0.0074 0.0008 0.000000 0.000000
2459854 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 2.091192 2.905401 12.795624 13.774311 -0.109505 0.860952 -1.663388 -2.396952 0.7075 0.7389 0.4495 2.958963 2.546763
2459853 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.573063 2.390249 16.518311 17.670874 1.761878 2.120566 -1.943922 -3.095155 0.7241 0.6789 0.4453 3.467913 3.190201
2459852 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 2.751524 4.600523 16.019201 17.930810 7.600349 7.748574 10.669393 12.286929 0.8068 0.8115 0.2810 5.061433 5.313942
2459851 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.424535 5.721825 18.290166 18.712407 5.136981 19.531101 2.595111 12.554404 0.7383 0.7332 0.3645 2.947240 2.757466
2459850 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.756966 2.875865 15.622652 16.339374 2.289820 5.817607 -0.162938 5.688537 0.7264 0.7462 0.3676 3.055441 2.934204
2459849 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 2.462089 3.252888 31.426852 32.725173 1.455625 1.917992 -1.101786 -1.991814 0.7257 0.7377 0.3724 2.666661 2.601147
2459848 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 2.249655 3.252682 22.563517 23.646458 2.939821 5.694635 -1.884104 -2.397765 0.7063 0.7439 0.3900 3.020885 2.916021
2459847 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 2.259168 2.967894 21.219578 22.555682 3.552427 9.952180 -1.091694 -2.153773 0.7107 0.6777 0.4466 2.294399 2.126464
2459846 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 9.323195 10.686406 16.743820 18.225408 10.055065 9.471941 -0.553845 -1.246931 0.8334 0.6628 0.5100 5.889580 2.806949
2459845 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 3.599176 3.884000 28.685894 30.209084 2.852849 3.243865 -1.361721 -2.842054 0.7304 0.7494 0.3811 0.000000 0.000000
2459844 not_connected 100.00% 100.00% 100.00% 0.00% - - 30.002485 31.338418 77.490359 77.675570 9.441747 10.310696 26.926853 30.985971 0.0329 0.0312 0.0011 nan nan
2459843 not_connected 100.00% 0.66% 0.66% 0.00% 100.00% 0.00% 8.571797 9.063615 18.894662 18.882324 9.044108 13.570397 -3.467713 -3.625519 0.7234 0.7304 0.4032 3.199406 2.977271
2459842 not_connected 0.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.692769 1.065845 0.032863 -0.545466 -1.724607 -1.924796 -2.168986 -2.150311 0.7231 0.6295 0.2847 2.815679 2.653751
2459841 not_connected 100.00% 100.00% 100.00% 0.00% - - 63.247197 60.254380 72.102045 74.242901 58.350812 61.713181 43.956170 44.148228 0.0325 0.0318 0.0002 nan nan

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 48: 2459866

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
48 N06 not_connected nn Power 27.462191 3.233092 2.904472 27.462191 23.091020 1.527409 2.078619 -2.249529 -1.184372

Antenna 48: 2459865

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
48 N06 not_connected nn Power 36.936844 4.914315 3.896774 29.589316 36.936844 3.915458 6.198334 6.856215 5.697046

Antenna 48: 2459864

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
48 N06 not_connected nn Power 24.494026 9.348158 7.830430 24.494026 24.431078 8.947288 5.483175 -6.272246 -5.934556

Antenna 48: 2459863

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
48 N06 not_connected nn Shape 5.307999 4.299793 5.307999 4.147923 4.022896 1.585015 2.104827 -3.200759 -4.023477

Antenna 48: 2459862

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
48 N06 not_connected ee Power 29.464767 5.908738 7.002335 29.464767 29.267047 7.478318 12.620876 -2.536284 -3.092680

Antenna 48: 2459861

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
48 N06 not_connected nn Shape 3.716508 3.716508 3.109155 2.473712 2.833104 0.217655 0.585942 -4.402133 -3.900575

Antenna 48: 2459860

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
48 N06 not_connected ee Power 22.435510 4.590615 5.097160 22.435510 22.125633 10.323019 14.678188 -2.299890 -3.351786

Antenna 48: 2459859

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
48 N06 not_connected nn Shape 3.130500 3.061670 3.130500 2.915110 2.464707 0.835001 0.216629 -2.412524 -2.922979

Antenna 48: 2459858

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
48 N06 not_connected nn Shape 3.468368 3.468368 3.042627 2.294387 2.634102 -0.285007 0.585636 -4.508992 -4.229243

Antenna 48: 2459857

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
48 N06 not_connected nn Temporal Discontinuties 49.794054 24.319911 25.011257 11.234026 11.192288 12.644056 11.908282 49.794054 47.511844

Antenna 48: 2459856

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
48 N06 not_connected ee Power 20.579751 6.456241 6.571342 20.579751 20.140595 4.427210 7.416480 -3.855797 -4.192125

Antenna 48: 2459855

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
48 N06 not_connected nn Power inf 75.479274 75.881435 inf inf 4363.637796 4363.644384 4164.518655 4165.170593

Antenna 48: 2459854

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
48 N06 not_connected nn Power 13.774311 2.905401 2.091192 13.774311 12.795624 0.860952 -0.109505 -2.396952 -1.663388

Antenna 48: 2459853

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
48 N06 not_connected nn Power 17.670874 2.390249 1.573063 17.670874 16.518311 2.120566 1.761878 -3.095155 -1.943922

Antenna 48: 2459852

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
48 N06 not_connected nn Power 17.930810 2.751524 4.600523 16.019201 17.930810 7.600349 7.748574 10.669393 12.286929

Antenna 48: 2459851

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
48 N06 not_connected nn Temporal Variability 19.531101 1.424535 5.721825 18.290166 18.712407 5.136981 19.531101 2.595111 12.554404

Antenna 48: 2459850

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
48 N06 not_connected nn Power 16.339374 1.756966 2.875865 15.622652 16.339374 2.289820 5.817607 -0.162938 5.688537

Antenna 48: 2459849

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
48 N06 not_connected nn Power 32.725173 2.462089 3.252888 31.426852 32.725173 1.455625 1.917992 -1.101786 -1.991814

Antenna 48: 2459848

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
48 N06 not_connected nn Power 23.646458 3.252682 2.249655 23.646458 22.563517 5.694635 2.939821 -2.397765 -1.884104

Antenna 48: 2459847

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
48 N06 not_connected nn Power 22.555682 2.967894 2.259168 22.555682 21.219578 9.952180 3.552427 -2.153773 -1.091694

Antenna 48: 2459846

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
48 N06 not_connected nn Power 18.225408 9.323195 10.686406 16.743820 18.225408 10.055065 9.471941 -0.553845 -1.246931

Antenna 48: 2459845

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
48 N06 not_connected nn Power 30.209084 3.884000 3.599176 30.209084 28.685894 3.243865 2.852849 -2.842054 -1.361721

Antenna 48: 2459844

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
48 N06 not_connected nn Power 77.675570 30.002485 31.338418 77.490359 77.675570 9.441747 10.310696 26.926853 30.985971

Antenna 48: 2459843

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
48 N06 not_connected ee Power 18.894662 9.063615 8.571797 18.882324 18.894662 13.570397 9.044108 -3.625519 -3.467713

Antenna 48: 2459842

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
48 N06 not_connected ee Shape 1.692769 1.692769 1.065845 0.032863 -0.545466 -1.724607 -1.924796 -2.168986 -2.150311

Antenna 48: 2459841

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
48 N06 not_connected nn Power 74.242901 63.247197 60.254380 72.102045 74.242901 58.350812 61.713181 43.956170 44.148228
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